MVLR | Multivariate Linear Regression Calc | Machine Learning library

by SMH17 C Version: Current License: No License

X-Ray Key Features Code Snippets Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | MVLR Summary

MVLR is a C library typically used in Artificial Intelligence, Machine Learning applications. MVLR has no bugs, it has no vulnerabilities and it has low support. You can download it from GitHub.

Multivariate Linear Regression MVLR1.

Support

Quality

Security

License

Reuse

Support

MVLR has a low active ecosystem.

It has 2 star(s) with 2 fork(s). There are 2 watchers for this library.

It had no major release in the last 6 months.

MVLR has no issues reported. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of MVLR is current.

Quality

MVLR has 0 bugs and 0 code smells.

Security

MVLR has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

MVLR code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

MVLR does not have a standard license declared.

Check the repository for any license declaration and review the terms closely.

Without a license, all rights are reserved, and you cannot use the library in your applications.

Reuse

MVLR releases are not available. You will need to build from source code and install.

Top functions reviewed by kandi - BETA

kandi's functional review helps you automatically verify the functionalities of the libraries and avoid rework.
Currently covering the most popular Java, JavaScript and Python libraries. See a Sample of MVLR

Get all kandi verified functions for this library.

MVLR Key Features

No Key Features are available at this moment for MVLR.

MVLR Examples and Code Snippets

No Code Snippets are available at this moment for MVLR.

Community Discussions

Trending Discussions on MVLR

Existing python implementation of least-squares to find closest point to several hyperplanes?

QUESTION

Existing python implementation of least-squares to find closest point to several hyperplanes?

Asked 2020-Dec-02 at 16:58

This SO answer describes how to find the point closest to multiple lines in n-dimensional space using the least-squares method. Is there any existing implementation of this, but for the point closest to multiple m-flats in n-dimensional space?

My use case is that I used Multivariate Linear Regression to determine a relationship between an independent variable vector x and a dependent variable vector y, and now I'd like to find x that would make the stochastic process output values as closes as possible to experimental data y_exp. Since running MvLR yields a set of n-dimensional equations like so...

...and I have experimental values for y_1, ... y_q, each of these equations represents the intersection between two (n-1)-flat in n-dimensional space (one described by equation (1), and the other by y_1 = y_exp_1), which should yield an (n-2)-flat.

Is there an existing implementation to find a good set of x_1, ... x_p that gets me closest to these (n-2)-flats?

...

ANSWER

Answered 2020-Dec-02 at 16:58

Rather than interpreting the set of equations like that, you could see it as a simple set of q linear equations with p variables -- in which case the problem has a much easier solution!

This set of equations is 100% equivalent to...

where:

In which case the least squares approximation method yields...

Assuming the rank of matrix A is equal to q (i.e., you have enough linearly independent equations to solve the problem, which is probably respected if your data is experimental), then this is equivalent to:

For an explanation on this, see this excellent video.

Python code:

Source https://stackoverflow.com/questions/65041868

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install MVLR

You can download it from GitHub.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

Find more information at: